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Diffstat (limited to 'extern/libmv/third_party/ceres/include/ceres/gradient_problem.h')
| -rw-r--r-- | extern/libmv/third_party/ceres/include/ceres/gradient_problem.h | 127 |
1 files changed, 0 insertions, 127 deletions
diff --git a/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h b/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h deleted file mode 100644 index 55a8be1df09..00000000000 --- a/extern/libmv/third_party/ceres/include/ceres/gradient_problem.h +++ /dev/null @@ -1,127 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2014 Google Inc. All rights reserved. -// http://code.google.com/p/ceres-solver/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#ifndef CERES_PUBLIC_GRADIENT_PROBLEM_H_ -#define CERES_PUBLIC_GRADIENT_PROBLEM_H_ - -#include "ceres/internal/macros.h" -#include "ceres/internal/port.h" -#include "ceres/internal/scoped_ptr.h" -#include "ceres/local_parameterization.h" - -namespace ceres { - -class FirstOrderFunction; - -// Instances of GradientProblem represent general non-linear -// optimization problems that must be solved using just the value of -// the objective function and its gradient. Unlike the Problem class, -// which can only be used to model non-linear least squares problems, -// instances of GradientProblem not restricted in the form of the -// objective function. -// -// Structurally GradientProblem is a composition of a -// FirstOrderFunction and optionally a LocalParameterization. -// -// The FirstOrderFunction is responsible for evaluating the cost and -// gradient of the objective function. -// -// The LocalParameterization is responsible for going back and forth -// between the ambient space and the local tangent space. (See -// local_parameterization.h for more details). When a -// LocalParameterization is not provided, then the tangent space is -// assumed to coincide with the ambient Euclidean space that the -// gradient vector lives in. -// -// Example usage: -// -// The following demonstrate the problem construction for Rosenbrock's function -// -// f(x,y) = (1-x)^2 + 100(y - x^2)^2; -// -// class Rosenbrock : public ceres::FirstOrderFunction { -// public: -// virtual ~Rosenbrock() {} -// -// virtual bool Evaluate(const double* parameters, -// double* cost, -// double* gradient) const { -// const double x = parameters[0]; -// const double y = parameters[1]; -// -// cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x); -// if (gradient != NULL) { -// gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x; -// gradient[1] = 200.0 * (y - x * x); -// } -// return true; -// }; -// -// virtual int NumParameters() const { return 2; }; -// }; -// -// ceres::GradientProblem problem(new Rosenbrock()); -class CERES_EXPORT GradientProblem { - public: - // Takes ownership of the function. - explicit GradientProblem(FirstOrderFunction* function); - - // Takes ownership of the function and the parameterization. - GradientProblem(FirstOrderFunction* function, - LocalParameterization* parameterization); - - int NumParameters() const; - int NumLocalParameters() const; - - // This call is not thread safe. - bool Evaluate(const double* parameters, double* cost, double* gradient) const; - bool Plus(const double* x, const double* delta, double* x_plus_delta) const; - - private: - internal::scoped_ptr<FirstOrderFunction> function_; - internal::scoped_ptr<LocalParameterization> parameterization_; - internal::scoped_array<double> scratch_; -}; - -// A FirstOrderFunction object implements the evaluation of a function -// and its gradient. -class CERES_EXPORT FirstOrderFunction { - public: - virtual ~FirstOrderFunction() {} - // cost is never NULL. gradient may be null. - virtual bool Evaluate(const double* const parameters, - double* cost, - double* gradient) const = 0; - virtual int NumParameters() const = 0; -}; - -} // namespace ceres - -#endif // CERES_PUBLIC_GRADIENT_PROBLEM_H_ |